README.Rmd

---
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# PLNmodels: Poisson lognormal models <img src="inst/sticker/PLNmodels.png" align="right" width="155" height="180"/>

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> The Poisson lognormal model and variants can be used for a variety of multivariate problems when count data are at play (including PCA for count data and network inference). This package implements an efficient algorithm to fit such models accompanied with a set of functions for vizualisation and diagnostic. Learn more in the vignettes: `vignette(package = "PLNmodels")`.

## Installation

### System Requirements

Installation requires a system version of [nlopt 2.4-2](https://nlopt.readthedocs.io/) 

- On Debian or Ubuntu use `libnlopt-dev`:

```{bash apt, eval = FALSE}
sudo apt-get install libnlopt-dev
```

- On Fedora or similar use `NLopt-devel`:

```{bash yum, eval = FALSE}
sudo yum install NLopt-devel
```

- With Mac OS X, install `nlopt` via [homebrew](https://brew.sh/)

```{bash brew, eval = FALSE}
brew install nlopt
```

- On Windows, the package now builds and installs correctly, by [including static libraries](https://github.com/rwinlib/nlopt) on compilation. However, I just test it with appveyor so I have never run PLNmodels on Windows: any feedbacks welcomed!

### R Package installation

```{r package, eval = FALSE}
## w/o vignettes
devtools::install_github("jchiquet/PLNmodels")
devtools::install_github("jchiquet/PLNmodels", build_vignettes = TRUE)
```

## References

Please cite our work using the following references:

- J. Chiquet, M. Mariadassou and S. Robin: Variational inference for probabilistic Poisson PCA, the Annals of Applied Statistics, to appear. [link](https://arxiv.org/abs/1703.06633)

- J. Chiquet, M. Mariadassou and S. Robin: Variational inference for sparse network reconstruction from count data, arXiv preprint, 2018. [link](https://arxiv.org/abs/1806.03120)